Un acercamiento al estudio de modelos predictivos para mover la forma en la que analizamos los negocios

1. How predictive modeling
change the world of business
Fabricio Quintanilla

3. Agenda
 Introduction to Big Data.
 What is Analytics?
 Overview of Predictive Analytics Techniques.
 Business Applications of Predictive Analytics.
 Predictive Analytics Tools in Market.

4. Gartner Hype Cycle

5. Things That Happen On Internet Every Sixty Seconds

6. Things That Happen Every Sixty Seconds

7. The 5 V's of Big Data
“Big data is high-volume, high-velocity and high-variety information assets
that demand cost-effective, innovative forms of information processing for
enhanced insight and decision making.”

8. Survey on Big Data Adoption Stages

9. What is Analytics?

10. OSEMN is an acronym that rhymes with “awesome”
Data Analysis: OSEMN Process
Obtain Data
Scrub Data
Explore Data
Model Data
iNterpret Results

11. Predictive analytics is the practice of extracting insights from the existing
data set with the help data mining, statistical modeling and machine
learning techniques and using it to predict unobserved/unknown events.
 Identifying cause-effect relationships across the variables from the
historical data.
 Discovering hidden insights and patterns with the help of data mining
techniques.
 Apply observed patterns to unknowns in the Past, Present or Future.
What is Predictive Analytics?

12. Predictive Analytics Process Cycle

13. • Regression:
Predicting output variable using its cause-effect relationship with input
variables. OLS Regression, GLM, Random forests, ANN etc.
• Classification:
Predicting the item class. Decision Tree, Logistic Regression, ANN, SVM,
Naïve Bayes classifier etc.
• Time Series Forecasting:
Predicting future time events given past history. AR, MA, ARIMA, Triple
Exponential Smoothing, Holt-Winters etc.
Common Predictive Analytics Methods

14. • Association rule mining:
Mining items occurring together. Apriori Algorithm.
• Clustering:
Finding natural groups or clusters in the data. K-means, Hierarchical,
Spectral, Density based EM algorithm Clustering etc.
• Text mining:
Model and structure the information content of textual sources.
Sentiment Analysis, NLP
Common Predictive Analytics Methods
(Cont.)

15.  Need to check predictive model’s out of sample performance.
 Model Assessment: Hit Rate, Gini Coefficient, K-S Chart, Confusion
Matrix, ROC Curve, Lift Chart, Gain Chart etc.
Evaluating Predictive Models

16. Business Applications of Predictive Analytics
Factory Failures
FinanceSmarter Healthcare
Multi-channel
sales
Telecom
Manufacturing
Traffic Control
Trading Analytics Fraud and Risk
Renewable
Energy
Spam Filters
Retail:Churn

17. Business Applications (Contd.)
• Supply Chain:
Simulate and optimize supply chain flows to reduce inventory.
• Customer Profiling:
Identify high valued customers and retain their loyalty.
• Pricing:
Identify the optimal price which will increase net profit.
• Human Resources:
Best Employees selection for particular tasks at optimal compensation. Employee churn retention.

18. • Renewable Energy:
Energy forecasting, electricity price forecasting, Predictive Maintenance,
Operational cost minimization.
• Financial Services:
Approval of credit cards/ loan applications based on credit scoring
models, Options pricing, Risk analysis etc.
• E-Commerce:
Identify cross-sell and upsell opportunities, increase transactions size,
maximize campaign's response based CRM data.
Business Applications (Cont.)

19. • Product Quality Control:
Detect product quality issues in advance and prevent them.
• Revenue Performance:
Identify key drivers of revenue generation and optimization of revenue.
• Fraud and Crime Detection:
Detect fraud , criminal activity, insurance claims, tax evasion and credit
card frauds.
• HealthCare:
Identify prevalence of particular disease to a patient based health
conditions.
Business Applications (Cont.)

20. Predictive Analytics Tools in Market

21. Demo Azure Machine Learning

22. Fabricio Quintanilla, MSc, PhD
fabricio.quintanilla@gmail.com
@fabrixq
/fquintanilla
http://www.inteligenciadenegocios.net
MCP, MCPD, MCTS